| 1 |
A Robust Infinite Gaussian Mixture Model and Its Application in Fault Detection of Nonlinear Multimode Processes
Pan Y, Xie L, Su HY, Luo L
Journal of Chemical Engineering of Japan, 53(12), 758, 2020 |
| 2 |
An on-line framework for monitoring nonlinear processes with multiple operating modes
Tan RM, Cong T, Ottewill JR, Baranowski J, Thornhill NF
Journal of Process Control, 89, 119, 2020 |
| 3 |
MULTIMODE NON-GAUSSIAN PROCESS MONITORING BASED ON LOCAL ENTROPY INDEPENDENT COMPONENT ANALYSIS
Zhong N, Deng XG
Canadian Journal of Chemical Engineering, 95(2), 319, 2017 |
| 4 |
Multimode Monitoring of Oxy-Gas Combustion Through Flame Imaging, Principal Component Analysis, and Kernel Support Vector Machine
Bai XJ, Lu G, Hossain MM, Yan Y, Liu S
Combustion Science and Technology, 189(5), 776, 2017 |
| 5 |
Orthogonal nonnegative matrix factorization based local hidden Markov model for multimode process monitoring
Wang F, Zhu HL, Tan S, Shi HB
Chinese Journal of Chemical Engineering, 24(7), 856, 2016 |
| 6 |
Key principal components with recursive local outlier factor for multimode chemical process monitoring
Song B, Tan S, Shi HB
Journal of Process Control, 47, 136, 2016 |
| 7 |
An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes
Yang YW, Ma YX, Song B, Shi HB
Chinese Journal of Chemical Engineering, 23(8), 1357, 2015 |
| 8 |
A novel multimode process monitoring method integrating LCGMM with modified LFDA
Ren SJ, Song ZH, Yang MY, Ren JG
Chinese Journal of Chemical Engineering, 23(12), 1970, 2015 |
| 9 |
Modeling and monitoring of multimode process based on subspace separation
Zhang YW, Wang C, Lu RQ
Chemical Engineering Research & Design, 91(5), 831, 2013 |
| 10 |
Monitoring of time-varying processes using kernel independent component analysis
Zhang YW, An JY, Zhang HL
Chemical Engineering Science, 88, 23, 2013 |
